How to Develop a Bilingual Voice Assistant

Developing a bilingual voice assistant that can handle both English and Tamil addresses the limitations of current commercial assistants. An initial approach using the fastText library for language identification proved ineffective because the underlying speech recognition system defaulted to English, providing inaccurate text for classification. A more successful method was developed using the Google Speech Recognition API's confidence score feature. This solution involves transcribing the same audio clip twice—once for English and once for Tamil—and then comparing the confidence scores returned for each attempt. The language associated with the higher confidence score is then selected, allowing the assistant to dynamically identify the spoken language and respond appropriately.